How to Scrape T&T Supermarket Prices

Start here

No banner to choose here, since there’s only one chain. Paste this into the Input tab of the T&T Scraper API, switch to JSON view, and hit Start.

{
  "search_terms": ["eggs", "milk", "chicken breast"],
  "postal_code": "V5X 0C4"
}

Same run over HTTP:

curl -X POST \
  "https://api.apify.com/v2/acts/sunny_eternity~tnt-grocery-scraper/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"search_terms": ["eggs", "milk"], "postal_code": "V5X 0C4"}'

Swap search_terms for categories to walk a section instead, like ["produce/fruits", "dairy-eggs"].

Read these three first

I’d rather you know these before you build something on the data than find out afterwards.

• Prices don’t vary by store. T&T serves one catalogue chain-wide. postal_code and locationId label each row with the resolved store, but the product data is the same across the chain. The Loblaw and Pattison Actors do vary prices by store; this one can’t, because T&T doesn’t.
• Sale data is absent. was_price is always null and is_on_sale always false in this version. The fields exist so rows stay schema-compatible with the other Actors, not because they carry anything. If your project needs promotions, that gap matters.
• comparable_unit_price is null a lot. T&T sells much of its produce by weight with no package size in the title, so there’s nothing to normalize. You get null instead of a guess. This shows up far more here than on the other Actors.

What comes back

{
  "store": "T&T Supermarket",  "name": "Seedless Green Grape (~2.5lb)",  "price": "4.99",  "unit_price": "per lb",  "location_name": "Marine Gateway",   // nearest store from postal code  "selling_type": "by_weight",   // by_weight - sold per pound  "was_price": null,   // T&T promos not exposed yet  "is_on_sale": false,  … 8 more fields}

That grape row is the null case in the wild: sold by the pound, no size in the title, so package_size and comparable_unit_price both come back empty while price and unit_price are perfectly good.

From Python

pip install apify-client, then:

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("sunny_eternity/tnt-grocery-scraper").call(run_input={
    "search_terms": ["bok choy", "shiitake", "gochujang"],
    "postal_code": "V5X 0C4",
})

rows = list(client.dataset(run["defaultDatasetId"]).iterate_items())

# Keep only rows you can actually compare on unit price.
comparable = [r for r in rows if r.get("comparable_unit_price") is not None]
print(len(comparable), "of", len(rows), "rows have a unit price")

From JavaScript

npm i apify-client, then:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('sunny_eternity/tnt-grocery-scraper').call({
  search_terms: ['bok choy', 'shiitake', 'gochujang'],
  postal_code: 'V5X 0C4',
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
const comparable = items.filter((i) => i.comparable_unit_price !== null);

Stores and coverage

Stores resolve from T&T’s own live pickup-locations API, so a location that opened last month works with no update to the Actor. Pass locationId to pin one, like "MGFS" for Marine Gateway in Vancouver. Since the catalogue is chain-wide, that changes the label on each row rather than the prices.

To price T&T against the Loblaw and Pattison banners on shared staples in one run, use the comparison API, which includes tnt by default.